Instructions to use Muhammadidrees/Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Muhammadidrees/Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Muhammadidrees/Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Muhammadidrees/Model") model = AutoModelForSequenceClassification.from_pretrained("Muhammadidrees/Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c55846686d68918bb333fea55bb0c66fba7ff4aa4b2c3f34145a521ddf4050c6
- Size of remote file:
- 27.9 MB
- SHA256:
- 0614fe83cadab421296e664e1f48f4261fa8fef6e03e63bb75c20f38e37d07d3
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